I. Background and Objective：
This research project is to study the 10,000 residential AMI pilot deployments, and analyze potential benefits on energy efficiency and system operations through the development of energy management and time-of-use incentive programs. The project includes 8 tasks: (1) provide consulting and advisory services to support the AMI pilot deployment, (2) support the system specifications development after the vendor was selected, (3) conduct the technology assessment on the pilot system, (4) conduct the time-of-use and demand response trials, (5) conduct AMI cost benefit analysis, including potential benefits from distribution management system, customer energy efficiency, demand response, etc., (6) support the development of MDMS interface and value-added applications, (7) evaluate the AMI disaster recovery site strategy, and (8) assess the overall success of the pilot deployment.
The project consulting team members, including experts from Quanta Technology &
Nexant, based on their direct experience on large scale AMI implementation in USA, provided essential technical support to the TPC’s AMI team. Their supports included the technical consultation, acceptance testing, specification development, and technical documents reviews.
They also provided suggestions on testing platform, wireless communication solutions, data
transmission / throughput, system usability, stability, openness, expandability, and the consistency for large scale deployment.
In the project, the interfaces to MDMS and possible value-added applications were analyzed. A customer portal demonstration system was developed to evaluate the possibility of implementing these value-added services in the future large scale AMI system.
Based on the demand response trial programs that were agreed by TPC, the consulting team evaluated the feasibility of using demand response to assist future T&D operation and mitigate peak-demand usages
As part of the project tasks, a comprehensive cost benefit framework was developed. Based on the data provided by the vendors and data approved by TPC, the cost benefit analysis of AMI pilot system was conducted.
II. Research Results and Applications Overall, from the point of view of technology assessment, the 10,000 residential AMI deployment can be considered as a successful pilot project. It has been a great learning experience for TPC and the AMI vendors in Taiwan. The 10,000 AMI pilot system was tested according to the system procurement contract. The consulting team also provided additional suggestions on testing scopes.
Figure 1 below shows the communication
Technical Consultation, Assessment, and Cost/Benefit Analysis of the Residential AMI Pilot Deployment
（Load Research Laboratory ： Wang, Chin-Tun 、
Huang, Chia-Wen、Chen, Yuh-Ching、Jar, Fang-Pei）
architecture of the 10,000 AMI pilot system.
Figure 1: Communication Architecture of the 10,000 AMI Pilot System
The consulting team suggests that the future AMI communication should leverage TPC’s existing fiber network to ensure a fast and effective deployment. There are two system architecture designs that can be both implemented.
Considering the different technical characteristics between RF and PLC, there is no need to combine both solutions in one single data concentrator architecture.
Example 1: Based on RF Communication
[smart meter] --- RF mesh LAN--- [data concentrator] --- distribution network (if needed) --- [substation] --- fiber network --- [control center]
Example 2: Based on PLC
[smart meter] --- (LV) PLC --- [data concentrator]
--- distribution network --- [substation] --- fiber network --- [control center]
In the future, for the large scale system implementation, the consulting team suggested to conduct Request for Information (RFI) and then, Request for Proposal (RFP). From the RFI, TPC can obtain the state-of-the-art technologies and then those new technologies can be incorporated into the RFP. The AMI solution is an emerging technology that new solutions are becoming available through the years. It is suggested that the future RFP should define the functional requirements and performance metrics, rather than detailed specifications.
The consulting team suggested TPC to revisit the business application and data transmission requirements that were originally listed in the earlier RFP for the 10,000 meter pilot. Too many or redundant data collection and transmission can increase the burden of communication network as
well as the energy consumption of smart meters (and other AMI devices), and hence, increase the operation cost. The consulting team provided the recommendations on the future 100,000 meter implementation RFP. The future RFP should include overall system architecture, smart meters, communication systems, head-end systems, system integration, interoperability requirements, maintenance and upgrade. In the original 10,000 pilot specifications, there was lack of overall system performance testing and end-to-end data integrity verifications. The consulting team also provided suggestions on performance metrics that can be included in the future RFP to address those areas. It was also suggested that in the future vendor selection, TPC should focus in technical assessment and evaluate each proposed solutions carefully. As for the commercial evaluation, TPC should assess the Total Cost of Ownership (TOC), i.e. besides the initial capital cost, TPC should include the future 5-10 years operation and maintenance costs in the consideration.
In the pilot project, there was a critical gap – lack of testing environment. The AMI vendors in Taiwan do not have sufficient testing facility to perform Factory Acceptance Tests (FAT). As a result, all the system level tests were performed in the field (i.e. TPC system). This is not appropriate.
In principle, the vendor and TPC should first conduct the FAT at vendor’s facility; then conduct the Site Acceptance Tests (SAT) in the TPC field.
Missing the FAT steps increased the risk of the system implementation. Going forward, TPC should review what testing facilities in Taiwan (e.g. III, ITRI, TPC, etc.) are currently available and develop a plan to establish an AMI testing lab.
This will help future AMI technology assessment, and test the applicability of new solutions in
Taiwan. The AMI testing lab may be expanded into a smart grid lab.
In this project, a comprehensive cost benefit analysis framework was developed. The consulting team used the cost data provided by Tatung and system parameters approved by TPC to estimate the cost benefit of the pilot system and perform analyses.
Based on the international experiences of the consulting team members, the purpose of a small pilot system is usually on technology assessment on smart metering, communication solutions, system performance, etc. The value from the lessons learned in a pilot system implementation is far more important than the actual cost benefit calculated from the data. A small pilot implementation benefit cost ratio is usually relatively low.
In this project, the benefit cost ratio is 0.5124.
Monte Carlo simulations were used to analyze the impacts from the uncertainties of each parameter.
Figure 2 shows the results from one million runs.
The average benefit cost ratio is 0.61566, the mean value is 0.604, maximum value is 1.414, and the minimum is 0.328. The most common occurrence is between 0.56 and 0.58, with 80,054 times out of one million runs, there is 0.196% that the cost benefit ratio is greater than 1.0.
Figure 2: Benefit / Cost Ration from One Million Runs
As one of the project tasks, the researchers also established demand response and TOU testing programs and the validation procedure.
From program design, customer survey, public
presentation, registration, enrollment portal, to final result analyses, the entire life cycle of demand response testing provided TPC valuable information for future experiment. The experiences would help TPC’s future demand response implementation. The summary of two tested tariff programs, peak time rebate (PTR) and critical peak pricing (CPP) are listed in the table below. The researchers used region, household income, customer classifications as segmentation parameters and applied decision tree analysis to find potential customers for the tested programs.
PTR Program CPP Program
Enrollment rate (customer number)
6.6%(102 customer) 8.42%(697 customer)
Peak Load Reduction About 2.3% About 5.6%
Participation Rate
About 50% of the enrolled customers were willing to participate and change power usage behavior. The average peak load reduction was about 8.82%
About 80% of the enrolled customers were willing to participate and change power usage behavior. The average peak load reduction was about 11.25%
Regional Reduction Effects
Taipei is 7.2%；
Taichung is 14%
Taipei and New Taipei are 11%；
Ma-Kong is 5%
Class of Customer Reduction Effects
> 1000kWh/bill customer are 6%, 700 –1000kWh/bill customers are 12%。
> 1000kWh/bill customers are 13.5%, the other are about 10%.
Reduction vs Rebate More related to the willingness to participate
Need to go higher than NT$ 8.59 to see significant reduction
Difficulty to Implement
Baseline establishment Calculation of appropriate rebate
In order to maximize the benefits of large
scale deployment of AMI, TPC needs to realize the potential applications of the data in MDMS, such as outage management, load analysis, customer usage data, grid operations and planning. Smart meter data offers TPC new opportunities to improve the reliability and performance of their distribution systems.
Volt-VAR, conservation voltage reduction, load balancing, outage management, transformer overload detection and even high impedance fault detection could benefit significantly from smart meter data. However, TPC should perform the following foundational activities to use smart meter data for grid operations: (a) get an accurate M-T-P map of the circuit, (b) determine required meter data for the application, (c) have a Time-of-Day communications load profile, and (d) use transform application for power outage, restoration alert.
In this pilot project, the TPC’s AMI team worked diligently; reviewed all documentations and technical details. The lessons learned will have great benefits to the future deployment.
The consulting team suggested that when the AMI deployment is more than one million meters, TPC should consider setting up an AMI operation center in the future. The AMI operation center can provide a collaboration platform for experts from various departments. It will perform system monitoring, data collection, network event management, billing and support to other back-office system interfaces.
